Cydonia-24B-v4.3-JANG_2M
Released by mobbitxt in 2026, Cydonia-24B-v4.3-JANG_2M is a 24 billion parameter chat model. Cydonia-24B-v4.3-JANG_2M is an open-weights chat model with roughly 24 billion parameters.
by mobbitxt · 24B parameters
Best for
Ways to use Cydonia-24B-v4.3-JANG_2M in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your mobbitxt API key. osFoundry discovers Cydonia-24B-v4.3-JANG_2M automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Cydonia-24B-v4.3-JANG_2M is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run Cydonia-24B-v4.3-JANG_2M
Cydonia-24B-v4.3-JANG_2M runs on a single 16GB consumer GPU (~15 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~58 GB).
Cydonia-24B-v4.3-JANG_2M vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Cydonia-24B-v4.3-JANG_2M
Is Cydonia-24B-v4.3-JANG_2M free to use?
Cydonia-24B-v4.3-JANG_2M is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Cydonia-24B-v4.3-JANG_2M commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Cydonia-24B-v4.3-JANG_2M need?
Approximately 15 GB at Q4 quantisation, or 58 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Cydonia-24B-v4.3-JANG_2M locally?
Yes. Cydonia-24B-v4.3-JANG_2M is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Cydonia-24B-v4.3-JANG_2M best at?
Cydonia-24B-v4.3-JANG_2M is well-suited to text generation.
How do I use Cydonia-24B-v4.3-JANG_2M in osFoundry?
Paste your mobbitxt API key in the key dialog (or deploy the open weights for self-hostable models), assign Cydonia-24B-v4.3-JANG_2M to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by mobbitxt on March 25, 2026. Source: https://huggingface.co/mobbitxt/Cydonia-24B-v4.3-JANG_2M